plotMD: plotMD

In mcalgaro93/benchdamic: Benchmark of differential abundance methods on microbiome data

plotMD

Description

A function to plot mean difference (MD) and zero probability difference (ZPD) values between estimated and observed values.

Usage

plotMD(data, difference = NULL, split = TRUE)

Arguments

data	a list, output of the fitModels function. Each element of the list is a 'data.frame' object with Model, Y, Y0, MD, and ZPD columns containing the model name, the observed values for the mean and the zero proportion and the differences between observed and estimated values.
difference	character vector, either MD or ZPD to plot the differences between estimated and observed mean counts or the differences between estimated zero probability and observed zero proportion.
split	Display each model mean differences in different facets (default split = TRUE). If FALSE, points are not displayed for more clear representation.

Value

a ggplot object.

See Also

fitModels and RMSE for the model estimations and the RMSE computations respectively. plotRMSE for the graphical evaluation of the RMSE values.

Examples

# Generate some random counts
counts = matrix(rnbinom(n = 600, size = 3, prob = 0.5), nrow = 100, ncol = 6)

# Estimate the counts assuming several distributions
GOF <- fitModels(
    object = counts, models = c(
        "NB", "ZINB",
        "DM", "ZIG", "HURDLE"
    ), scale_HURDLE = c("median", "default")
)

# Plot the results
plotMD(data = GOF, difference = "MD", split = TRUE)
plotMD(data = GOF, difference = "ZPD", split = TRUE)

mcalgaro93/benchdamic documentation built on March 10, 2024, 10:40 p.m.